Image-based features in machine learning to identify delivery errors and predict error magnitude for patient-specific IMRT quality assurance

OBJECTIVE: To identify delivery error type and predict associated error magnitude by image-based features using machine learning (ML). METHODS: In this study, a total of 40 thoracic plans (including 208 beams) were selected, and four error types with different magnitudes were introduced into the ori...

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Detalles Bibliográficos
Autores principales: Huang, Ying, Pi, Yifei, Ma, Kui, Miao, Xiaojuan, Fu, Sichao, Chen, Hua, Wang, Hao, Gu, Hengle, Shao, Yan, Duan, Yanhua, Feng, Aihui, Zhuo, Weihai, Xu, Zhiyong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10133379/
https://www.ncbi.nlm.nih.gov/pubmed/36988665
http://dx.doi.org/10.1007/s00066-023-02076-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10133379/
https://www.ncbi.nlm.nih.gov/pubmed/36988665
http://dx.doi.org/10.1007/s00066-023-02076-8

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